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概要と使いどころ
Expert patterns for Godot 3D physics (Jolt/PhysX), including Ragdolls, PhysicalBones, Joint3D constraints, RayCasting optimizations, and collision layers. Use for rigid body simulations, character physics, or complex interactions. Trigger keywords: RigidBody3D, PhysicalBone3D, Jolt, Ragdoll, Skeleton3D, Joint3D, PinJoint3D, HingeJoint3D, Generic6DOFJoint3D, RayCast3D, PhysicsDirectSpaceState3D.
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Expert blueprint for educational games including gamification loops (learn/apply/feedback/adapt), progress tracking (student profiles, mastery %), adaptive difficulty (target 70% success rate), spaced repetition, curriculum trees (prerequisite system), and visual feedback (confetti, XP bars). Use for learning apps, training simulations, or edutainment. Trigger keywords: educational_game, gamification, adaptive_difficulty, spaced_repetition, student_profile, curriculum_tree, mastery_tracking.
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Expert blueprint for romance games and dating sims (Tokimeki Memorial, Monster Prom, Persona social links) focusing on affection systems, multi-stat relationships, dated events, and route branching. Use when building relationship-centric games, social simulations, or otome games. Keywords romance, dating sim, affection system, relationship stats, date events, character routes, love interest.
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Expert patterns for simplifying 3D games to 2D including dimension reduction strategies, 2.5D fake-depth, isometric ports, camera flattening, physics conversion, 3D-to-sprite art pipeline, and control simplification. Use when porting 3D to 2D, building 2.5D / isometric / fake-depth gameplay, creating 2D versions for mobile, or prototyping. Trigger keywords: CharacterBody3D to CharacterBody2D, Camera3D to Camera2D, Vector3 to Vector2, flatten Z-axis, 2.5D, isometric, fake depth, Y-sort, simulated Z, orthogonal projection, 3D to sprite conversion, performance optimization.
日本語の概要は準備中です。原文の説明を表示しています。
Verify UI *workflow* correctness that a task list, code review, and static screenshots miss. Drives end-to-end user flows in the Simulator via XCUITest with per-step screenshots, statically audits the navigation graph for dead-ends and missing edit paths, and emits a human discoverability checklist. Use after building any phase/slice that adds or changes UI, or when a user reports "I could only figure out the flow by running it."
日本語の概要は準備中です。原文の説明を表示しています。
A robust and outlier-aware method for testing differential tissue composition from single-cell data. This model can infer changes in tissue composition and heterogeneity, and can produce realistic data simulations based on any existing dataset. This model can also transfer knowledge from a large set of integrated datasets to increase accuracy further.
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We present a statistical simulator, scDesign3, to generate realistic single-cell and spatial omics data, including various cell states, experimental designs, and feature modalities, by learning interpretable parameters from real data. Using a unified probabilistic model for single-cell and spatial omics data, scDesign3 infers biologically meaningful parameters; assesses the goodness-of-fit of inferred cell clusters, trajectories, and spatial locations; and generates in silico negative and positi
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This package provides a collection of functions designed for analyzing deconvolution of the bulk sample(s) using an atlas of reference omic signature profiles and a user-selected model. Users are given the option to create or extend a reference atlas and,also simulate the desired size of the bulk signature profile of the reference cell types.The package includes the cell-type-specific methylation atlas and, Illumina Epic B5 probe ids that can be used in deconvolution. Additionally,we included BS
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Microbiome time series simulation with generalized Lotka-Volterra model, Self-Organized Instability (SOI), and other models. Hubbell's Neutral model is used to determine the abundance matrix. The resulting abundance matrix is applied to (Tree)SummarizedExperiment objects.
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Friday bulk football matchday simulations on MiroShark - pay $1 USDC per sim via x402 (Finance District agent wallet), launch Premier League, Serie A, and La Liga matchday sims in parallel, collect share links and full reports, and render or hand off one video per sim.
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Generate, simulate, audit, and deploy a Uniswap v4 hook + test pool from a brief, on any Uniswap v4 chain (every testnet and mainnet) - pre-audited templates or a from-scratch freeform hook (flags auto-derived; static audit + dangerous-pattern scan + a behavioral forge test + fork sim gate the deploy). Dry-run by default; explicit arm: to broadcast; testnet default, mainnet behind a double opt-in; records the deploy to main. Every deployed hook inherits a mandatory 10 bps AeonFee protocol fee.
日本語の概要は準備中です。原文の説明を表示しています。
Step 5 of the PaperOrchestra pipeline (arXiv:2604.05018). Iteratively refine drafts/paper.tex by simulating peer review and applying targeted revisions, with strict accept/revert halt rules, deterministic 0-100 decision bands (Accept/Minor/Major/Reject) that drive a target-met early stop, and a Devil's Advocate concession-threshold guard that blocks acceptance on unresolved critical findings. Maintains a worklog and snapshots each iteration so revert is real, not symbolic. TRIGGER when the orchestrator delegates Step 5 or when the user asks to "refine the draft", "iterate on the paper", or "run peer review on this paper".
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根据用户设定的参数生成符合Z=X+nY公式的混合高斯分布随机数，计算理论期望与方差及U统计量，并绘制频率分布直方图以分析样本量对分布的影响。
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模拟 CentOS Linux 7 终端行为（含 Synopsys VCS/UVM 环境），仅输出代码块结果，不进行解释。
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The consumer panel. Spins up a swarm of buyer sub-agents (default 100, --quick for 20) trained on the user's target customer, each with a different income, age, buying behaviour and objection, shows every one the same pitch, and runs the business through 100 buyer scenarios to see who buys, who doesn't, and why. Tallies the answers into buy rates by segment, the reasons people pass in their own words, what would flip a no, and price answers for founder-pricing. Use when the user says "would people buy this", "test it on customers", "run the consumer panel", "simulate buyers", "who is my customer", or "validate demand".
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Your marketing director. Turns the buyer panel and the competitor map into positioning, the channels the target customer actually uses, a 30-day launch campaign with dated posts and ads, the first ten hooks, a budget split and the numbers to watch. Every message answers an objection real or simulated buyers raised. Use when the user says "how do I market this", "marketing plan", "launch campaign", "how do I get customers", "where do I advertise", "write my ads", or "positioning".
日本語の概要は準備中です。原文の説明を表示しています。
Your launch lead. Builds a dated, step-by-step launch plan: a cheap real-world test first (a waitlist, a pre-sale or a pop-up with a real price, so real buyers confirm what the simulated panel said), then the countdown to opening day with owners and deadlines, the launch-day run sheet, and the first 30 days of what to measure and what to change. Use when the user says "how do I launch", "launch plan", "when can I open", "launch checklist", "go live", or "soft open".
日本語の概要は準備中です。原文の説明を表示しています。
Improve an explanation with a bounded critique-and-revision pass and unresolved-evidence notes. Use for this Bot Generator Bot template; creates drafts or simulations within its declared scope.
日本語の概要は準備中です。原文の説明を表示しています。
Draft Twilio messaging or voice workflow requests for separately authorized execution. Use for this Bot Generator Bot template; creates drafts or simulations within its declared scope.
日本語の概要は準備中です。原文の説明を表示しています。
Draft Google Sheets scripts or Excel macros with explicit test plans. Use for this Bot Generator Bot template; creates drafts or simulations within its declared scope.
日本語の概要は準備中です。原文の説明を表示しています。
Draft original songs, arrangement sketches and performance guidance. Use for this Bot Generator Bot template; creates drafts or simulations within its declared scope.
日本語の概要は準備中です。原文の説明を表示しています。
Design bounded bot specifications with clear purpose, examples, output contracts and error handling. Use for this Bot Generator Bot template; creates drafts or simulations within its declared scope.
日本語の概要は準備中です。原文の説明を表示しています。
Return brief playful positive, neutral or negative fortune game responses. Use for this Bot Generator Bot template; creates drafts or simulations within its declared scope.
日本語の概要は準備中です。原文の説明を表示しています。
Create study sessions using recall questions, chunking, mnemonics and explicit review intervals. Use for this Bot Generator Bot template; creates drafts or simulations within its declared scope.
日本語の概要は準備中です。原文の説明を表示しています。